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A Manipulator Can Aid Prediction Market Accuracy
Author(s) -
HANSON ROBIN,
OPREA RYAN
Publication year - 2009
Publication title -
economica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.532
H-Index - 65
eISSN - 1468-0335
pISSN - 0013-0427
DOI - 10.1111/j.1468-0335.2008.00734.x
Subject(s) - economics , incentive , variance (accounting) , preference , econometrics , boosting (machine learning) , microeconomics , computer science , artificial intelligence , accounting
Prediction markets are low volume speculative markets whose prices offer informative forecasts on particular policy topics. Observers worry that traders may attempt to mislead decision makers by manipulating prices. We adapt a Kyle‐style market microstructure model to this case, adding a manipulator with an additional quadratic preference regarding the price. In this model, when other traders are uncertain about the manipulator's target price, the mean target price has no effect on prices, and raising the variance of the target price can increase average price accuracy, by boosting the returns to informed trading and thereby incentives for traders to become informed.